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How to get a correct data analysis?
What does data analysis mean?
Since the field of data analysis is the field more exciting and influencing technology in our time, its goal is to simplify matters to the maximum extent of big data and come up with a specific goal and solution. The data analysis gives a visualization and guesswork of events, and helps in finding answers that can be sufficiently convincing for a specific issue or problem and researching it in order to finally reach an optimal conclusion and a completely convincing solution.
What are data analysis methods?
The first data analysis method is statistical analysis: It is done with some programs and certain commands, such as the famous Excel program.
The second data analysis method is descriptive analysis: It is through which research can be done with complete protection and logic to describe a specific phenomenon or information.
The third data analysis method is qualitative analysis: It is one of the branches of analytical chemistry, which is usually used in medicine and chemistry.
What is data analysis process?
Data analysis is the process of examining and checking the data, in order to be more accurate and correct, and to reshape it as required. Data analysis also includes the process of storing data as well in order to access reliable information in making and determining the desired decisions.
It can be said that data analysis has many methods that differ according to the field to which the researcher belongs. Data analysis is used in science, social sciences and finance as well.
What does the statistical analysis techniques mean?
Statistical analysis techniques include each science, a set of terms and vocabulary of its own, which familiarity with it is an important step on the road to study. The in-depth understanding of the topics of this science of statistical analysis, and the scale of evidence analysis techniques is not different in this regard from other sciences.
This scale is one of the tributaries of statistics. Researchers must be familiar with the basic terminology of statistical analysis techniques in order for them to know how to deal with statistical analysis techniques when they write their own scientific research.
The importance of the statistical analysis system
The statistical analysis system is one of the most important means in scientific research through the use of its rules, laws and methods in collecting data and information necessary in scientific research. This information is analyzed for the purpose of getting the results of the research. The statistical analysis system also has a prominent role in setting future plans by forecasting results for all sectors. Statistical analysis system can be applied in the fields of pure sciences or humanities.
We will provide examples of some of the areas in which statistics are used, which have had a prominent role in solving many of their problems:
- The statistical analysis system is used to develop education and its plans.
- The statistical analysis system is used to study various sciences.
- Statistical analysis system is used in the field of advertising and commercials.
- The statistical analysis system is widely used in the insurance field.
- Statistical analysis system is used in the field of economics, industry and others.
Data in statistical techniques
Data: Generally, data is a group of letters, words, numbers, symbols, or images related to a specific subject. An example of this: Student data (names- level numbers- division- specialization) without arrangement, and after processing this data results in what is called the term information. We distinguish two types of qualitative data, and quantitative data:
- Qualitative Data: It measures a characteristic of a particular phenomenon without taking numerical values, and is divided into two types: nominal and ordinal.
- Quantitative Data:They take integer or fractional numerical values according to the conditions of the case studied. It is also divided into two types which are period data and relative data.
Watch: How do we use Data Analysis
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